AB1416 WHAT IS THE FULL ECONOMIC COST OF DELAYED DIAGNOSIS OF AXIAL SPONDYLOARTHRITIS IN THE UK?
Authors: G. Xydopoulos, S. Howard Wilsher, F. Zanghelini, O. Afolabi, M. Mishra, R. Fordham
Journal: Annals of the Rheumatic Diseases (2022)

Background Axial Spondyloarthritis (AS) is an umbrella term for both inflammatory conditions known as Ankylosing Spondylitis and Non-radiographic Axial Spondyloarthritis. AS generally develops in younger people. Symptoms typically start in the late teenage years to early twenties (with the average age of onset being 24). Hence this condition has a life-long impact, which could increase if left untreated. Average delay to diagnosis is over eight years after the appearance of symptoms. There are currently 220,000 people in the UK living with this painful and progressive form of inflammatory arthritis. While people wait for a diagnosis, many withdraw from socialising and find it harder to establish careers, form relationships, and start families. In addition to healthcare costs, that include multiple visits to GPs, prescription of unnecessary medication and extensive use of over the counter painkillers, there are intangible costs that have large impacts on patients and society. For example, quality of life for the patient, their earning and saving for retirement capacity, social care costs. Objectives To determine the full economic cost, including medical productively loss and other out of pocket related costs of delayed diagnosis for AS in the UK. Methods We are building an economic Markov model to determine a total cost per patient per year of delay. The model will project disease progression forward in time-steps with feedback loops to allow movement in states back and forth. Transition states within each time-step will be constructed according to the various stage of the disease and they will be used primarily to demonstrate an assessment of the costs in the time taken to a confirmed diagnosis. The model will capture symptoms and impacts of AS leading up to that diagnosis and before initiation of treatment. Assuming the one-year maximum ‘gold standard’ time to diagnosis that NASS would like to see to, the sum of costs prior to this in each consecutive cycle will be estimated. The inputs will consist of the average delay to diagnosis per gender and age group, the health resources utilisation, the cost of managing the symptoms, cost related to productivity losses and any other parameters and costs reflecting real resources required to diagnose, confirm, treat, cope with, manage and accommodate AS symptoms. Data include anonymised diagnosed patient data with the pathways they followed pre-diagnosis shared under strict confidentiality data sharing agreement from the secondary health units participating in the project. Cost data gathered from national sources and research into AS, NHS unit costs reports, productivity related reports and interviews with people with AS and clinicians providing valuable insight into the condition. The model will be validated by experts in the field and sufferers of AS to ensure accurate representation of actual events. Results The results will be provided at the conference and this is work in progress. A preliminary analysis of anonymised data of the pathway of 513 people towards an AS diagnosis show that the delay on female patients is slightly longer (mean of 9.85 years) compared to male patients (mean of 9.39 years). In both genders the delay is higher if the patient present symptom after the age of 31 years increasing the mean of previous age groups by 5 to 9 yrs. Table 1. Female Male Age Group Obs. Mean 95% CI Obs. Mean 95% CI 0-15 1 1 - 2 1.00 0.00, 13.71 16-30 49 3.59 2.69, 4.49 144.00 4.01 3.45, 4.57 31-45 50 11.72 9.64, 13.80 161.00 9.61 8.58, 10.65 46-60 24 18.17 13.05, 23.28 60.00 15.90 13.30, 18.50 61+ 3 17.33 0.00, 52.58 19.00 28.58 21.14, 36.02 Conclusion The results will help the National Axial Spondyloarthritis Society (NASS) to build an economic case for earlier diagnosis. The interactive model will support decision making in the future by allowing assumptions to be changed e.g., changing prices over time; varying wage rates depending on staff and skill mix; and the anticipated scale of savings in actual practice. References [1]Standfield et al. (2014). Markov Modelling and DES in health care: a comparison. Journal of technology Assessment in Health C 30 (2) 166-172 Acknowledgements With thanks to the National Axial Spondyloarthritis Society for commissioning this research and special thanks to Dale Webb and Jill Hamilton for their valuable support to contact clinician and sufferers of AS and for accessing necessary data. Importantly, thank you to the clinicians and sufferers of AS for their contribution to the research. Disclosure of Interests None declared